Rebuilding data in a dispersed storage network

ABSTRACT

A method for execution by a rebuilding module includes detecting that less than a pillar width number of encoded data slices of a common revision are retrievable from a set of storage units. A decode threshold number of encoded data slices are retrieved and decoded to reproduce a data segment. The data segment is encoded to produce at least one encoded data slice and storage of the at least one encoded data slice in the set of storage units is facilitated in accordance with the common revision when determining to rebuild the at least one encoded data slice. The data segment is encoded to reproduce the set of encoded data slices and storage of the reproduced set of encoded data slices is facilitated in the set of storage units in accordance with a new revision when determining to not rebuild the at least one encoded data slice.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility patent application claims priority pursuant to35 U.S.C. § 120 as a continuation of U.S. Utility application Ser. No.15/822,873, entitled “REBUILDING DATA IN A DISPERSED STORAGE NETWORK”,filed Nov. 27, 2017, which is a continuation-in-part of U.S. Utilityapplication Ser. No. 15/400,092, entitled “MODIFYING INFORMATIONDISPERSAL ALGORITHM CONFIGURATIONS IN A DISPERSED STORAGE NETWORK”,filed Jan. 6, 2017, issued as U.S. Pat. No. 10,057,351 on Aug. 18, 2021,which is a continuation-in-part of U.S. Utility application Ser. No.15/223,707, entitled “AVOIDING WRITE CONFLICTS IN A DISPERSED STORAGENETWORK”, filed Jul. 29, 2016, issued as U.S. Pat. No. 10,013,471 onJul. 3, 2018, which is a continuation of U.S. Utility application Ser.No. 13/959,702, entitled “WRITING DATA AVOIDING WRITE CONFLICTS IN ADISPERSED STORAGE NETWORK”, filed Aug. 5, 2013, issued as U.S. Pat. No.9,424,326 on Aug. 23, 2016, which claims priority pursuant to 35 U.S.C.§ 119(e) to U.S. Provisional Application No. 61/700,691, entitled“UPDATING A DISPERSED STORAGE AND TASK NETWORK INDEX”, filed Sep. 13,2012, all of which are hereby incorporated herein by reference in theirentirety and made part of the present U.S. Utility patent applicationfor all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention; and

FIG. 10 is a logic diagram of an example of a method of rebuilding datain accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

In various embodiments, each of the storage units operates as adistributed storage and task (DST) execution unit, and is operable tostore dispersed error encoded data and/or to execute, in a distributedmanner, one or more tasks on data. The tasks may be a simple function(e.g., a mathematical function, a logic function, an identify function,a find function, a search engine function, a replace function, etc.), acomplex function (e.g., compression, human and/or computer languagetranslation, text-to-voice conversion, voice-to-text conversion, etc.),multiple simple and/or complex functions, one or more algorithms, one ormore applications, etc. Hereafter, a storage unit may be interchangeablyreferred to as a dispersed storage and task (DST) execution unit and aset of storage units may be interchangeably referred to as a set of DSTexecution units.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each managing unit 18 and the integrity processing unit 20 maybe separate computing devices, may be a common computing device, and/ormay be integrated into one or more of the computing devices 12-16 and/orinto one or more of the storage units 36. In various embodiments,computing devices 12-16 can include user devices and/or can be utilizedby a requesting entity generating access requests, which can includerequests to read or write data to storage units in the DSN.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-8. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN memory 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an 10 interface module 60, at least one 10 device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. Here, the computing device stores data object40, which can include a file (e.g., text, video, audio, etc.), or otherdata arrangement. The dispersed storage error encoding parametersinclude an encoding function (e.g., information dispersal algorithm(IDA), Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides dataobject 40 into a plurality of fixed sized data segments (e.g., 1 throughY of a fixed size in range of Kilo-bytes to Tera-bytes or more). Thenumber of data segments created is dependent of the size of the data andthe data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 80 is shown inFIG. 6. As shown, the slice name (SN) 80 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of another embodiment of a dispersedstorage network (DSN) system that includes a storage unit set 386 and arebuilding module 388. The rebuilding module 388 can include at leastone processor and/or a memory, and can be implemented using one or moreof a computing device, a server, a user device, the storage integrityunit 20 FIG. 1, a storage integrity module, a dispersed storage (DS)processing unit, a DS processing module, a DS unit, a distributedstorage and task (DST) processing module, the DS client module 34 ofFIG. 1, the computing device 16 of FIG. 1, and/or the storage unit 36 ofFIG. 1. The storage unit set 386 includes a set of storage units 354that are utilized to store one or more sets of encoded data slices,where a data segment is encoded using a dispersed storage error codingfunction to produce the one or more sets of encoded data slices. Some orall of the set of storage units can be implemented by utilizing thestorage unit 36 of FIG. 1.

The system can function to remedy a storage error (e.g., missing encodeddata slice, corrupted encoded data slice) associated with an encodeddata slice stored within a storage unit 354 of the set of storage units.The rebuilding module 388 detects the storage error of the encoded dataslice of a corresponding set of encoded data slices associated with thestorage unit of the set of storage units. The detecting includes atleast one of a scanning for storage errors, receiving an error message,and receiving a rebuilding request. The rebuilding module 388 selects adecode threshold number of storage units as rebuilding participants 390.The selecting includes identifying available storage units 354 of theset of storage units and selecting from the available storage unitsthose storage units associated with other encoded data slices of the setof encoded data slices, where the other encoded data slices are notassociated with storage errors.

The rebuilding module 388 issues partial slice requests 392 to eachstorage unit of the rebuilding participants 390, where each partialslice request 392 includes one or more of an identifier of the encodeddata slice associated with the storage error, identifiers of therebuilding participants, a rebuilding matrix, an encoding matrix, apublic key of a public/private key pair of the rebuilding module, and apartial rebuild package routing ordering (e.g., including a destinationfor sending a partial rebuild package).

A rebuilding participant (e.g., hereafter interchangeably referred to asa storage unit 354), of the rebuilding participants 390, generates azero information gain partial slice. The generating the zero informationgain partial slice includes obtaining an encoding matrix utilized togenerate the encoded data slice (e.g., extract from a received partialslice request, retrieve from a memory), reducing the encoding matrix toproduce a square matrix that exclusively includes rows identified in thepartial slice request (e.g., include a decode threshold number of rowsassociated with the rebuilding participants), inverting the squarematrix to produce an inverted matrix (e.g., alternatively, may extractthe rebuilding matrix from the partial slice request as the invertedmatrix), matrix multiplying the inverted matrix by an associated encodeddata slice held by the rebuilding participant (e.g., of the otherencoded data slices of the set of encoded data slices) to produce avector, and matrix multiplying the vector by a row of the encodingmatrix corresponding to the encoded data slice to be rebuilt (e.g.,alternatively, may extract the row from the partial slice request), toproduce the zero information gain partial slice.

The rebuilding participant encrypts the zero information gain partialslice using the public key of the rebuilding module and a homomorphicencryption algorithm to produce an encrypted zero information gainpartial slice. Homomorphic encryption enables operations to be performedon ciphertexts, which remain intact upon decryption. For example, if Aand B are two plaintext numbers, an “additively” homomorphic encryptionsystem is one in which Decryption(Encryption(A)+Encryption(B))=A+B.Examples include the Paillier cryptosystem and the Goldwasser-Micalicryptosystem. Thus, two encrypted ciphertexts can be added and whendecrypted with the appropriate key, the result is the same as ifplaintexts A and B had been added.

The rebuilding participants and/or the rebuilding module combines acorresponding encrypted zero information gain partial slice from each ofthe rebuilding participants to produce a partial rebuild package 394.The combining includes one or more of combining a received partialrebuild package 394 from another rebuilding participant with theencrypted zero information gain partial slice to produce another partialrebuild package and sending the other partial rebuild package 394 to yetanother rebuilding participant in accordance with the partial rebuildpackage routing ordering. For example, a second storage unit of therebuilding participants receives a partial rebuild package 394 from afirst storage unit 354 of the rebuilding participants 390, combines thereceived partial rebuild package from the first storage unit with itsown encrypted zero information gain partial slice to produce the otherpartial rebuild package 394 to send to a third storage unit 354 of therebuilding participants 390.

The combining of the received partial rebuild package 394 from the otherrebuilding participant with the encrypted zero information gain partialslice includes finding the sum of the partials in the field. Forexample, the received partial rebuild package is exclusiveOR-ed with theencrypted zero information gain partial. Depending on the field, summingmay be exclusiveOR (XOR) or it may be another form of addition (e.g.,such as addition modulo a prime). For example, some implementations ofShamir secret sharing, for example, perform all addition andmultiplication modulo some prime. In such a case, instead of using XORthe summing may be accomplished by combining the partials via modularaddition (e.g., which is how addition is defined in that field ofintegers). Such an approach may require a minor change to how theencryption of the partials works. Instead of combining the partial witha keystream via XOR, one rebuilding participant would add the key stream(e.g., according to rules of addition in the field) such that anotherrebuilding participant using a corresponding key would subtract the samekeystream from a partial associated with the other rebuildingparticipant. In fields where XOR represents addition, it also representssubtraction, so all participants handle combining identically. In analternate field of integers where addition was not identical tosubtraction, then rebuilding participants must agree on a conventionwhere a first rebuilding participant subtracts and a second rebuildingparticipant adds. For example, the convention may include adeterministic approach where whichever rebuilding participant has alower index number for the encoded data slice/share they hold adds andanother rebuilding participant associated with a higher index numbersubtracts.

A last storage unit 354 of the rebuilding participants 390 generates anoutput and associated partial rebuild package 394 as a rebuild package396 to the rebuilding module 388, where the rebuild package 396 includesa combination of each of a decode threshold number of encrypted zeroinformation gain partial slices from each of the rebuildingparticipants. The rebuilding module 388 decrypts the rebuild package 396using a private key of the public/private key pair of the rebuildingmodule 388 to produce a rebuilt slice 398. The rebuilding module 388facilitates storage of the rebuilt slice 398 in the storage unit 354associated with the storage error. For example, the rebuilding module388 sends the rebuilt slice 398 to a seventh storage unit 354 forstorage.

To rebuild data, a rebuilding module can scan for slices to rebuild bycomparing responses to listing requests from storage units. If aparticular revision of a slice is found on less than a full width ofstorage units or stores of a DSN module, the rebuilding module can thendetermine what information dispersal algorithm (IDA) configuration wasused for that slice to determine if the source is recoverable or not.This determination can be made by reading at least one of the slicesand/or by checking its IDA identifier which is represented in the slicedata. Based on the IDA identifier, the rebuilding module can determinewhat the IDA threshold is, can retrieve at least a threshold number ofslices, and can decode the slices to obtain the source data. If thewidth of the IDA configuration is the maximum, the rebuilding module canrebuild the slices and keep the revision the same. If, however, thewidth is less than the maximum width, the rebuilder can rebuild allslices, for example, by choosing a new revision number, and can use theIDA configuration having the greatest width. At this point therebuilding module can finalize the slices, for example, by removing theprevious revisions of slices.

In various embodiments, a processing system a rebuilding module includesat least one processor and a memory that stores operationalinstructions, that when executed by the at least one processor cause theprocessing system to detect that less than a pillar width number ofencoded data slices of a set of encoded data slices of a common revisionare retrievable from a set of storage units. Dispersal parametersassociated with the set of encoded data slices are identified, where thedispersal parameters include a decode threshold number. The decodethreshold number of encoded data slices are retrieved when the less thanthe pillar width number of encoded data slices includes at least thedecode threshold number of encoded data slices. The decode thresholdnumber of encoded data slices are decoded to reproduce a data segment.The processing system determines whether to rebuild at least one encodeddata slice based on determining whether combining the at least oneencoded data slice with the less than the pillar width number of encodeddata slices reforms a full pillar width number of encoded data slices.The data segment is encoded to produce the at least one encoded dataslice and storage of the at least one encoded data slice in the set ofstorage units is facilitated in accordance with the common revision whenit is determined to rebuild the at least one encoded data slice. Thedata segment is encoded to reproduce the set of encoded data slices andstorage of the reproduced set of encoded data slices is facilitated inthe set of storage units in accordance with a new revision when it isdetermined to not rebuild the at least one encoded data slice.

In various embodiments, the data segment was dispersed storage errorencoded to produce the set of encoded data slices for storage in the setof storage units. In various embodiments, detecting that less than thepillar width number of encoded data slices are retrievable includesinvoking a list query to the set of storage units and comparing queryresponses received from the set of storage units. In variousembodiments, identifying the dispersal parameters includes reading anencoded data slice of the set of encoded data slices and extracting thedispersal parameters from the encoded data slice. In variousembodiments, retrieving the decode number of encoded data slicesincludes generating at least the decode threshold number of read slicerequests for transmission to the set of storage units, and receiving theat least the decode threshold number of encoded data slices from the setof storage units in response.

In various embodiments, determining whether to rebuild the at least oneencoded data slice is further based on the dispersal parameters and areliability goal. In various embodiments, the reliability goal indicatesto provide the full pillar width of encoded data slices, where the atleast one encoded data slice is determined to be rebuilt in response todetermining that a dispersal parameter pillar width is less than thefull pillar width.

In various embodiments, facilitating storage of the at least one encodeddata slice includes, for each slice of the at least one encoded dataslice, generating a write slice request that includes the encoded dataslice and a revision number of the common revision. In variousembodiments, facilitating storage of the reproduced set of encoded dataslices includes generating a set of write slice requests that includesthe set of encoded data slices and a new revision number.

FIG. 10 is a flowchart illustrating an example of rebuilding data. Inparticular, a method is presented for use in association with one ormore functions and features described in conjunction with FIGS. 1-9, forexecution by a processing system of a rebuilding module that includes aprocessor and memory, by a distributed storage and task (DS) clientmodule of a computing device that includes a processor, and/or viaanother processing system of a dispersed storage network that includesat least one processor and memory that stores instruction that configurethe processor or processors to perform the steps described below.

The method begins at step 600 where a processing system (e.g., of adistributed storage and task (DS) client module) detects that less thana pillar width number of encoded data slices of a set of encoded dataslices of a common revision are retrievable from a distributed storageand task network (DSTN) module, a set of storage units such as storageunit set 386 of FIG. 9, and/or another module that includes a memorythat stores encoded data slices. The detecting can include at least oneof receiving a message, invoking a list query, and/or comparing queryresponses. The method continues at step 602 where the processing systemidentifies dispersal parameters associated with a set of encoded dataslices. The identifying can include at least one of performing aregistry lookup, reading at least one encoded data slice of the set ofencoded data slices, and/or extracting the dispersal parameters from theat least one encoded data slice. The identified dispersal parameters caninclude a decode threshold number.

When the less then the pillar width number of encoded data slicesincludes at least a decode threshold number of encoded data slices, themethod continues at step 604 where the processing system retrieves theat least the decode threshold number of encoded data slices. Theretrieving can include generating at least a decode threshold number ofread slice requests for any available decode threshold number of encodeddata slices of the set of encoded data slices, outputting the at leastthe decode threshold number of reads slice requests to the DSTN moduleand/or the set of storage units, and/or receiving the least the decodethreshold number of encoded data slices.

The method continues at step 606 where the processing system decodes thedecode threshold number of encoded data slices using a dispersed storageerror coding function in accordance with the dispersal parameters toreproduce a data segment. The method continues at step 608 where theprocessing system determines whether to rebuild one or more encoded dataslices based on determining whether combining the one or more encodeddata slices with the less than the pillar width number of encoded dataslices reforms a full pillar width number of encoded data slices. Thedetermining can be based on one or more of the dispersal parameters, amemory availability indicator, a reliability goal, a performance goal, arequest, a lookup, and/or a predetermination. For example, theprocessing system determines to rebuild the one or more encoded dataslices when a reliability goal indicates to always provide a full pillarwidth number of encoded data slices. The method branches to step 614when the processing system determines not to rebuild the one or moreencoded data slices. The method continues to step 610 when theprocessing system determines to rebuild the one or more encoded dataslices.

The method continues at step 610 where the processing system encodes thedata segment using the dispersed storage error coding function inaccordance with the dispersal parameters to produce the one or moreencoded data slices. The method continues at step 612 where theprocessing system facilitates storing the one or more encoded dataslices in the DSTN module associated with the common revision and/or theset of storage units in accordance with the common revision. Thefacilitating can include, for each slice of the one or more encoded dataslices, generating a write slice request that includes the encoded dataslice and/or a revision number of the common revision.

The method continues at step 614 where the processing system encodes thedata segment using the dispersed storage or coding function inaccordance with the dispersal parameters to reproduce the set of encodeddata slices (e.g., full pillar width set) when the processing systemdetermines not to rebuild the one or more encoded data slices. Themethod continues at step 616 where the processing system facilitatesstoring the reproduced set of encoded data slices in the DSTN moduleassociated with a new revision and/or the set of storage units inaccordance with the new revision. The facilitating can includegenerating a set of write slice requests that includes the set ofencoded data slices and/or a new revision number.

In various embodiments, a non-transitory computer readable storagemedium includes at least one memory section that stores operationalinstructions that, when executed by a processing system of a dispersedstorage network (DSN) that includes a processor and a memory, causes theprocessing system to detect that less than a pillar width number ofencoded data slices of a set of encoded data slices of a common revisionare retrievable from a set of storage units. Dispersal parametersassociated with the set of encoded data slices are identified, where thedispersal parameters include a decode threshold number. The decodethreshold number of encoded data slices are retrieved when the less thanthe pillar width number of encoded data slices includes at least thedecode threshold number of encoded data slices. The decode thresholdnumber of encoded data slices are decoded to reproduce a data segment.The processing system determines whether to rebuild at least one encodeddata slice based on determining whether combining the at least oneencoded data slice with the less than the pillar width number of encodeddata slices reforms a full pillar width number of encoded data slices.The data segment is encoded to produce the at least one encoded dataslice and storage of the at least one encoded data slice in the set ofstorage units is facilitated in accordance with the common revision whenit is determined to rebuild the at least one encoded data slice. Thedata segment is encoded to reproduce the set of encoded data slices andstorage of the reproduced set of encoded data slices is facilitated inthe set of storage units in accordance with a new revision when it isdetermined to not rebuild the at least one encoded data slice.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing system”, “processingmodule”, “processing circuit”, “processor”, and/or “processing unit” maybe used interchangeably, and may be a single processing device or aplurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing system, processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing system, processing module, module,processing circuit, and/or processing unit. Such a memory device may bea read-only memory, random access memory, volatile memory, non-volatilememory, static memory, dynamic memory, flash memory, cache memory,and/or any device that stores digital information. Note that if theprocessing system, processing module, module, processing circuit, and/orprocessing unit includes more than one processing device, the processingdevices may be centrally located (e.g., directly coupled together via awired and/or wireless bus structure) or may be distributedly located(e.g., cloud computing via indirect coupling via a local area networkand/or a wide area network). Further note that if the processing system,processing module, module, processing circuit, and/or processing unitimplements one or more of its functions via a state machine, analogcircuitry, digital circuitry, and/or logic circuitry, the memory and/ormemory element storing the corresponding operational instructions may beembedded within, or external to, the circuitry comprising the statemachine, analog circuitry, digital circuitry, and/or logic circuitry.Still further note that, the memory element may store, and theprocessing system, processing module, module, processing circuit, and/orprocessing unit executes, hard coded and/or operational instructionscorresponding to at least some of the steps and/or functions illustratedin one or more of the Figures. Such a memory device or memory elementcan be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by a rebuilding module that includes a processor, the method comprises: when less than a pillar width number of a set of encoded data slices of a common revision are retrievable from a set of storage units, identifying dispersal parameters associated with the set of encoded data slices, wherein the dispersal parameters include a decode threshold number; retrieving the decode threshold number of encoded data slices when the less than the pillar width number includes at least the decode threshold number of encoded data slices; decoding the decode threshold number of encoded data slices to reproduce a data segment; determining whether to rebuild at least one encoded data slice based on determining whether combining the at least one encoded data slice with the less than the pillar width number of encoded data slices reforms a full pillar width number of encoded data slices; encoding the data segment to produce the at least one encoded data slice and facilitating storage of the at least one encoded data slice in the set of storage units in accordance with the common revision when it is determined to rebuild the at least one encoded data slice; and encoding the data segment to reproduce the set of encoded data slices and facilitating storage of the reproduced set of encoded data slices in the set of storage units in accordance with a new revision when it is determined to not rebuild the at least one encoded data slice.
 2. The method of claim 1, wherein the data segment was dispersed storage error encoded to produce the set of encoded data slices for storage in the set of storage units.
 3. The method of claim 1, further comprising: detecting when less than the pillar width number of encoded data slices are retrievable by invoking a list query to the set of storage units and comparing query responses received from the set of storage units.
 4. The method of claim 1, wherein identifying the dispersal parameters includes reading an encoded data slice of the set of encoded data slices and extracting the dispersal parameters from the encoded data slice.
 5. The method of claim 1, wherein retrieving the decode threshold number of encoded data slices includes generating at least the decode threshold number of read slice requests for transmission to the set of storage units, and receiving the at least the decode threshold number of encoded data slices from the set of storage units in response.
 6. The method of claim 1, wherein determining whether to rebuild the at least one encoded data slice is further based on the dispersal parameters and a reliability goal.
 7. The method of claim 6, wherein the reliability goal indicates to provide the full pillar width of encoded data slices, wherein the at least one encoded data slice is determined to be rebuilt in response to determining that a dispersal parameter pillar width is less than the full pillar width.
 8. The method of claim 1, wherein facilitating storage of the at least one encoded data slice includes, for each slice of the at least one encoded data slice, generating a write slice request that includes the encoded data slice and a revision number of the common revision.
 9. The method of claim 1, wherein facilitating storage of the reproduced set of encoded data slices includes generating a set of write slice requests that includes the set of encoded data slices and a new revision number.
 10. A processing system of a rebuilding module comprises: at least one processor; a memory that stores operational instructions, that when executed by the at least one processor cause the processing system to: when less than a pillar width number of a set of encoded data slices of a common revision are retrievable from a set of storage units, identify dispersal parameters associated with the set of encoded data slices, wherein the dispersal parameters include a decode threshold number; retrieve the decode threshold number of encoded data slices when the less than the pillar width number of encoded data slices includes at least the decode threshold number of encoded data slices; decode the decode threshold number of encoded data slices to reproduce a data segment; determine whether to rebuild at least one encoded data slice based on determining whether combining the at least one encoded data slice with the less than the pillar width number of encoded data slices reforms a full pillar width number of encoded data slices; encode the data segment to produce the at least one encoded data slice and facilitate storage of the at least one encoded data slice in the set of storage units in accordance with the common revision when it is determined to rebuild the at least one encoded data slice; and encode the data segment to reproduce the set of encoded data slices and facilitate storage of the reproduced set of encoded data slices in the set of storage units in accordance with a new revision when it is determined to not rebuild the at least one encoded data slice.
 11. The processing system of claim 10, wherein the data segment was dispersed storage error encoded to produce the set of encoded data slices for storage in the set of storage units.
 12. The processing system of claim 10, wherein the operational instructions, when executed by the at least one processor, cause the processing system to: detect when less than the pillar width number of encoded data slices are retrievable by invoking a list query to the set of storage units and comparing query responses received from the set of storage units.
 12. The processing system of claim 10, wherein identifying the dispersal parameters includes reading an encoded data slice of the set of encoded data slices and extracting the dispersal parameters from the encoded data slice.
 13. The processing system of claim 10, wherein retrieving the decode threshold number of encoded data slices includes generating at least the decode threshold number of read slice requests for transmission to the set of storage units, and receiving the at least the decode threshold number of encoded data slices from the set of storage units in response.
 14. The processing system of claim 10, wherein determining whether to rebuild the at least one encoded data slice is further based on the dispersal parameters and a reliability goal.
 15. The processing system of claim 15, wherein the reliability goal indicates to provide the full pillar width of encoded data slices, wherein the at least one encoded data slice is determined to be rebuilt in response to determining that a dispersal parameter pillar width is less than the full pillar width.
 16. The processing system of claim 10, wherein facilitating storage of the at least one encoded data slice includes, for each slice of the at least one encoded data slice, generating a write slice request that includes the encoded data slice and a revision number of the common revision.
 17. The processing system of claim 10, wherein facilitating storage of the reproduced set of encoded data slices includes generating a set of write slice requests that includes the set of encoded data slices and a new revision number.
 19. A computer readable storage medium comprises: at least one memory section that stores operational instructions that, when executed by a processing system of a dispersed storage network (DSN) that includes a processor and a memory, causes the processing system to: when less than a pillar width number of a set of encoded data slices of a common revision are retrievable from a set of storage units, identify dispersal parameters associated with the set of encoded data slices, wherein the dispersal parameters include a decode threshold number; retrieve the decode threshold number of encoded data slices when the less than the pillar width number of encoded data slices includes at least the decode threshold number of encoded data slices; decode the decode threshold number of encoded data slices to reproduce a data segment; determine whether to rebuild at least one encoded data slice based on determining whether combining the at least one encoded data slice with the less than the pillar width number of encoded data slices reforms a full pillar width number of encoded data slices; encode the data segment to produce the at least one encoded data slice and facilitate storage of the at least one encoded data slice in the set of storage units in accordance with the common revision when it is determined to rebuild the at least one encoded data slice; and encode the data segment to reproduce the set of encoded data slices and facilitate storage of the reproduced set of encoded data slices in the set of storage units in accordance with a new revision when it is determined to not rebuild the at least one encoded data slice.
 20. The computer readable storage medium of claim 19, wherein facilitating storage of the reproduced set of encoded data slices includes generating a set of write slice requests that includes the set of encoded data slices and a new revision number. 